def test_Identity(par):
"""Dot-test, forward and adjoint for Identity operator
"""
Iop = Identity(par['ny'], par['nx'], dtype=par['dtype'])
assert dottest(Iop, par['ny'], par['nx'], complexflag=0 if par['imag'] == 0 else 3)
x = np.ones(par['nx']) + par['imag'] * np.ones(par['nx'])
y = Iop*x
x1 = Iop.H*y
assert_array_almost_equal(x[:min(par['ny'], par['nx'])],
y[:min(par['ny'], par['nx'])], decimal=4)
assert_array_almost_equal(x[:min(par['ny'], par['nx'])],
x1[:min(par['ny'], par['nx'])], decimal=4)
def test_Affine(par):
"""Affine set projection and proximal/dual proximal of related indicator
"""
Op = Identity(par['nx'])
b = np.random.normal(0., 1., par['nx'])
aff = AffineSet(Op, b, 10)
# prox
tau = 2.
x = np.ones(par['nx'])
assert_array_almost_equal(aff.prox(x, tau), b)
# prox / dualprox
assert moreau(aff, x, tau)
def test_Identity_inplace(par):
"""Dot-test, forward and adjoint for Identity operator"""
np.random.seed(10)
Iop = Identity(par["ny"], par["nx"], dtype=par["dtype"], inplace=True)
assert dottest(Iop,
par["ny"],
par["nx"],
complexflag=0 if par["imag"] == 0 else 3)
x = np.ones(par["nx"]) + par["imag"] * np.ones(par["nx"])
y = Iop * x
x1 = Iop.H * y
assert_array_almost_equal(x[:min(par["ny"], par["nx"])],
y[:min(par["ny"], par["nx"])],
decimal=4)
assert_array_almost_equal(x[:min(par["ny"], par["nx"])],
x1[:min(par["ny"], par["nx"])],
decimal=4)
def test_Identity_noinplace(par):
"""Dot-test, forward and adjoint for Identity operator (not in place)
"""
np.random.seed(10)
Iop = Identity(par['ny'], par['nx'], dtype=par['dtype'], inplace=False)
assert dottest(Iop, par['ny'], par['nx'],
complexflag=0 if par['imag'] == 0 else 3)
x = np.ones(par['nx']) + par['imag'] * np.ones(par['nx'])
y = Iop*x
x1 = Iop.H*y
assert_array_almost_equal(x[:min(par['ny'], par['nx'])],
y[:min(par['ny'], par['nx'])], decimal=4)
assert_array_almost_equal(x[:min(par['ny'], par['nx'])],
x1[:min(par['ny'], par['nx'])], decimal=4)
# change value in x and check it doesn't change in y
x[0] = 10
assert x[0] != y[0]
def create_data2D():
"""Create 2d dataset"""
t0_plus = np.array([0.02, 0.08])
t0_minus = t0_plus + 0.04
vrms = np.array([1400.0, 1800.0])
amp = np.array([1.0, -0.6])
p2d_minus = hyperbolic2d(x, t, t0_minus, vrms, amp, wav)[1].T
kx = np.fft.ifftshift(np.fft.fftfreq(parmod["nx"], parmod["dx"]))
freq = np.fft.rfftfreq(parmod["nt"], parmod["dt"])
Pop = -PhaseShift(vel_sep, 2 * zrec, parmod["nt"], freq, kx)
# Decomposition operator
Dupop = Identity(parmod["nt"] * parmod["nx"]) + Pop
p2d = Dupop * p2d_minus.ravel()
p2d = p2d.reshape(parmod["nt"], parmod["nx"])
return p2d, p2d_minus
def test_Kroneker_Derivative(par):
"""Use Kronecker operator to apply the Derivative operator over one axis
and compare with FirstDerivative(... dir=axis)
"""
Dop = FirstDerivative(par['ny'], sampling=1, edge=True, dtype='float32')
D2op = FirstDerivative(par['ny'] * par['nx'],
dims=(par['ny'], par['nx']),
dir=0,
sampling=1,
edge=True,
dtype='float32')
Kop = Kronecker(Dop,
Identity(par['nx'], dtype=par['dtype']),
dtype=par['dtype'])
x = np.zeros((par['ny'], par['nx'])) + \
par['imag']*np.zeros((par['ny'], par['nx']))
x[par['ny'] // 2, par['nx'] // 2] = 1
y = D2op * x.flatten()
yk = Kop * x.flatten()
assert_array_equal(y, yk)
